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%\usepackage{bookman} % the used font
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%	TITLE PAGE
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\title[EfficientNet] %optional
{EfficientNet 在能量重建的应用}

%\subtitle{A short story by 何维}

\author[何杰汉, 何维] 
{何杰汉 \and 何维}

\institute{中山大学物理学院}

\date[JUNO]{2021/9/9}

\logo{\includegraphics[height=1cm]{figures/SYSU-logo.jpg}}

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\begin{document}



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\begin{frame}
\frametitle{\ 目\ 录}
\tableofcontents
\end{frame}




\section{网络介绍}

\begin{frame}
\frametitle{EfficientNet\ 思路来源}

作者
\footnote{Tan, Mingxing, and Quoc Le. "Efficientnet: Rethinking model scaling for convolutional neural networks." International Conference on Machine Learning. PMLR, 2019.}
发现分别调整模型的
\textcolor{red}{width, deepth, image resolution}
三个维度的参数可以优化模型的性能，联合调整可以获得最优的模型。

\begin{figure}
  \centering
  \includegraphics[width=.8\textwidth]{figures/cam.png}
  \caption{调整不同参数后的CAM(Class Activation Map)图
  \footnote{Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., and Torralba, A. Learning deep features for discriminative localization. CVPR, pp. 2921–2929, 2016.}
  }
\end{figure}

\end{frame}



\begin{frame}
\frametitle{实现方法
  \footnote{https://ai.googleblog.com/2019/05/efficientnet-improving-accuracy-and.html\\ }
}
\begin{itemize}
  \item 在小数据集上进行网格搜索(Grid Search)找出三个维度之间的关系
  
  \vspace{1em}
  \item 找出最合适参数组合之间的比例系数
  
  \vspace{1em}
  \item 使用比例系数修改模型，达到最优
  
\end{itemize}
\end{frame}



\begin{frame}
\frametitle{模型结构}
\begin{figure}
  \centering
  \includegraphics[width=.8\textwidth]{figures/struct-en-text.png}
  \caption{EfficientNet-B0 结构
    \footnote{Tan, Mingxing, and Quoc Le. "Efficientnet: Rethinking model scaling for convolutional neural networks." International Conference on Machine Learning. PMLR, 2019.}
  }
\end{figure}

\end{frame}



\begin{frame}
\frametitle{MBConv 结构}
\begin{columns}

  \column{.4\textwidth}
  \begin{block}{SEBlock}
    \vspace{2em}
    \begin{itemize}
      \item[-] GlobalAveragePooling2D
      \item[-] Conv2D
      \item[-] Conv2D   
    \end{itemize}
    \vspace{2em}
  \end{block}

  \column{.4\textwidth}
  \begin{block}{MBConv}
    \begin{itemize}
      \item[-] Conv2D
      \item[-] BatchNormalization
      \item[-] DepthWiseConv2D
      \item[-] BatchNormalization
      \item[-] SEBlock
      \item[-] Conv2D
      \item[-] Dropout       
    \end{itemize}
  \end{block}

\end{columns}

\vspace{2em}
From GitHub
\footnote{https://github.com/calmisential/EfficientNet\_TensorFlow2\\}

\end{frame}


\begin{frame}
\frametitle{\ 效\ 果}
\begin{figure}
  \centering
  \includegraphics[width=.65\textwidth]{figures/compare-net.png}
  \caption{EfficientNet和其它网络的对比
    \footnote{Tan, Mingxing, and Quoc Le. "Efficientnet: Rethinking model scaling for convolutional neural networks." International Conference on Machine Learning. PMLR, 2019.}
  }
\end{figure}
\end{frame}




\section{移植过程}

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\alert{使用\ Python 3.8.8, tensorflow 2.3.0, CUDA 10.2, cudnn 10.1}
  
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\section{Related work}

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\section{Proposed method}

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\frac{1}{f(x)},\ f(x) \neq 0 \\
f(x), \ f(x)=0
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\end{equation}

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\section{Experiments}

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The dataset information is shown in Fig. \ref{dataset}.
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\hline
Metrics   &   M1 &	M2	\\
\hline
Accuracy  &  87\% &	88\%	\\
Precision &  91\% &	90\%	\\
Recall	  & 75\% &	77\%	\\
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\section{Conclusion}

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\begin{thebibliography}{99} % Beamer does not support BibTeX so references must be inserted manually as below
\bibitem{team2015common}
Team, C.: Common vulnerability scoring system v3. 0: Specification document.
  First. org  (2015)
  
\bibitem{eiram2013cvssv2}
Eiram, C., Martin, B.: The cvssv2 shortcomings, faults, and failures
  formulation. In: Technical report, Forum of Incident Response and Security
  Teams (FIRST) (2013)
  
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